Data Scientist – Graph Analytics and Machine Learning- Anuview Remote Full-time
Full time @Data Science Career in Data Science , in Data Scientist Shortlist Email JobJob Detail
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Job ID 21318
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Sector Data Science
Job Description
Summary:
VIAVI (NASDAQ: VIAV) has a 90+ year history of technical innovations that have evolved to keep pace and address our customer’s most pressing business issues. We make equipment, software, and systems that help to plan, deploy, certify, monitor, and optimize all kinds of networks – like those for mobile phones, service providers, large businesses and data centers.
We are the people behind the products that help keep the world connected – at home, school, work, at play, and everywhere in between. VIAVI employees are fierce about supporting customer success and we welcome people who bring their best every day to the company – to question, to collaborate and to push for solutions that will delight our customers.
Duties & Responsibilities:
Are you a highly skilled Data Scientist with a passion for leveraging cutting-edge technologies to uncover insights from complex and diverse data sources? Are you drawn to exciting domains that are rich in data from disparate sources across a multitude of measurement points, that embody much latent information?
We are seeking a talented individual to join our team as a Data Scientist specializing in Graph Analytics and Machine Learning. As a key member of our data analytics team, you will play a pivotal role in developing innovative solutions that extract valuable knowledge from interconnected data sets and contribute to the data-driven decision-making processes of VIAVI and our customers.
Responsibilities:
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Utilize your expertise in data technologies, database management systems, and graph DBMS to design and implement efficient data storage, retrieval, and processing solutions.
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Apply your knowledge of machine learning techniques, graph methods, and neural networks to develop predictive models and uncover patterns in heterogeneous data sets.
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Lead graph-based learning initiatives by developing and implementing algorithms and methodologies to extract insights from complex networks and interconnected data sources.
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Perform time-series analysis to identify trends and patterns over temporal data, providing actionable insights for strategic planning.
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Develop and implement network analysis systems to extract actionable insights about relationships, connections, and dynamics within intricate data structures.
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Collaborate with cross-functional teams to identify and characterise business problems that can be addressed through advanced analytics and provide commercialisable data-driven solutions.
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Work autonomously and demonstrate the ability to handle projects with minimal supervision, from problem formulation to model deployment.
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Stay updated with the latest developments in data science, graph analytics, and machine learning, and contribute your knowledge to the team’s continuous improvement efforts.
Pre-Requisites / Skills / Experience Requirements:
Qualifications and Experience:
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Proven relevant experience (ideally 5+ years) including utilizing data technologies, database management systems, and graph DBMS for real-world projects.
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Strong background in machine learning, statistical methods, and neural networks, with a track record of developing and implementing predictive models.
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Expertise in graph-based learning techniques, and experience in processing and analysing interconnected data sets.
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Proficiency in time-series analysis techniques and familiarity with network analysis concepts.
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Experience in cloud machine learning platforms such as Amazon SageMaker, Microsoft Azure Machine Learning or Google Vertex AI would be an advantage.
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Demonstrated ability to work independently and deliver high-quality results with minimal supervision.
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Excellent problem-solving skills, a detail-oriented mindset, and a passion for uncovering insights from complex data.
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Strong programming skills in languages such as Python, and using relevant ML libraries.
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Familiarity with data visualization tools and libraries is a plus.
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Effective communication skills to present complex findings in a clear and concise manner to both technical and non-technical stakeholders.
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Demonstrated teamwork, strong planning and organizational skills.
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Some experience in aspects of the telecommunications domain would likely be an asset, although not essential.
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A Master’s degree in Computer Science, Data Science, Statistics, or a related field; PhD would be an advantage.
Join our dynamic team and contribute to shaping the future of data-driven decision-making through graph analytics and machine learning. Apply now to embark on an exciting journey of innovation and discovery.
Note: The qualifications and responsibilities listed above are intended to describe the general nature and level of work performed by individuals assigned to this position. They are not intended to be an exhaustive list of all responsibilities, duties, and skills required for the role.